Marker and kit for evaluating post-operation rejection risk of pancreas-kidney combined transplantation and application

Abstract

The invention relates to a marker and a kit for evaluating post-pancreas-kidney combined transplantation rejection risk and application, and belongs to the technical field of gene detection. According to the invention, 20 specific SNP site-methylation region combined markers are screened, and corresponding probes are designed for capturing free DNA covering SNP sites in a free DNA methylation library. Free DNA in blood of a patient is extracted, methylation conversion and library construction are carried out, a target SNP region is enriched through probe hybridization, and the DNA proportion and methylation level of a donor are analyzed in combination with high-throughput sequencing. By matching pancreas / kidney tissue methylation maps, the relative contents of pancreas-derived and kidney-derived free DNAs can be respectively calculated, so that the rejection risk of the two organs can be noninvasively and accurately evaluated. The kit comprises a biotin labeled probe, streptavidin magnetic beads and a sequencing primer, is suitable for rapid detection of clinical samples, and provides a reliable basis for early warning and individualized treatment of postoperative rejection.

Description

Technical Field

[0001] The present invention relates to the technical field of gene detection, in particular to a marker, a kit and an application for evaluating the rejection risk after simultaneous pancreas and kidney transplantation. Background Art

[0002] Simultaneous Pancreas and Kidney Transplantation (SPK) is the most effective method recognized internationally for treating diabetes mellitus combined with end-stage renal disease, which can provide long-term insulin independence and prevent the progression of diabetes-related complications. Although the clinical application of new immunosuppressants has significantly reduced the occurrence of postoperative complications, acute rejection remains the main problem affecting the long-term survival of grafts. Therefore, early monitoring of rejection is crucial. Currently, the clinical methods for detecting graft rejection mainly include pathological tissue examination and hematuria marker examination. Hematuria markers such as serum creatinine, serum lipase / amylase, and immune-related factors have poor sensitivity and latency in diagnosing early graft damage. Although tissue biopsy is the gold standard for diagnosing acute rejection, its clinical application is limited due to its invasiveness, risk of complications, and the fact that the test results rely on the subjective judgment of physicians. In addition, there are differences in the degree and type of rejection between the two organs in simultaneous pancreas and kidney transplantation. The risk of pancreatic graft biopsy is relatively high, and renal biopsy alone for SPK patients is not sufficient to determine the pathological status of the pancreatic graft. Therefore, there is an urgent need to establish a method that is both non-invasive and can achieve early and accurate monitoring of the rejection conditions of the donor pancreas and donor kidney respectively.

[0003] With the development of high-throughput sequencing technology, more and more studies have shown that donor-derived cell-free DNA (ddcfDNA) can be used as a marker for monitoring acute rejection after organ transplantation. DdcfDNA mainly comes from the necrosis, apoptosis or active secretion of donor cells, can reflect the degree of cell damage, and has the advantages of sensitivity, real-time and non-invasiveness. Most existing studies rely on the differences in single nucleotide polymorphism (SNP) or insertion / deletion (Indel) sites between the donor and recipient to identify the donor-derived part from cell-free DNA, and achieve high-precision quantification of ddcfDNA through the screening of candidate sites and the increase of sequencing depth. However, in simultaneous pancreas and kidney transplantation, since the grafts are from the same donor, the existing SNP / Indel-based ddcfDNA quantification methods can only determine the total proportion of donor origin, and cannot distinguish the proportions of the donor pancreas and donor kidney in the total cfDNA, thus unable to meet the need for separate monitoring of the graft conditions in SPK patients.

[0004] As a stable epigenetic modification, DNA methylation is cell- and tissue-specific, and the origin tissue can be traced according to the methylation pattern of cfDNA. The non-negative least squares (NNLS) method has been widely used in methylation-based tissue deconvolution problems. The basic assumption of this method is to regard the cfDNA methylation level as a linear combination of different tissue methylation levels on tissue markers, and then determine the composition ratio of different tissues in the sample through a quadratic programming algorithm. Although the NNLS deconvolution method based on the methylation map provides a feasible technical path for detecting the proportion of cfDNA from different grafts of the same donor in plasma, it still faces many challenges in practical applications. In particular, the error of this method is relatively large and the sensitivity needs to be improved. For patients with pancreas-kidney transplantation, due to the low content of cfDNA from the pancreas and kidney in plasma, the calculation results of the NNLS method are often inaccurate, which is very likely to lead to misjudgment of graft rejection. In addition, this method directly relies on the methylation level of different tissue-specific methylation regions in plasma for derivation, which usually requires sequencing methods such as whole-genome methylation sequencing covering a large number of cell / tissue-specific methylation regions, resulting in high sequencing costs, which greatly limits its wide application and in-depth development in clinical practice. Summary of the Invention

[0005] To solve the above technical problems, the present invention provides a combination of markers for evaluating the rejection risk after pancreas-kidney transplantation, screens out 20 specific SNP site-methylation region combined markers, and designs corresponding probes for capturing the free DNA covering the SNP sites in the free DNA methylation library. By extracting the free DNA in the patient's blood, performing methylation conversion and library construction, enriching the target SNP region by probe hybridization, and combining high-throughput sequencing to analyze the donor DNA ratio and methylation level. By matching the pancreas / kidney tissue methylation map, the relative contents of pancreas-derived and kidney-derived free DNA can be calculated respectively, so as to evaluate the rejection risk after pancreas-kidney transplantation.

[0006] The first object of the present invention is to provide a combined marker of SNP sites and methylation regions for evaluating the rejection risk after pancreas-kidney transplantation. The SNP sites include rs678476, rs7580884, rs200654741, rs4333131, rs57686994, rs1560173, rs13235115, rs1574122, rs797767, rs28972181, rs7142428, rs4074077, rs4395027, rs8026157, rs4984936, rs2303242, rs1107437, rs8064633, rs9912787, and rs7258301. The methylation region is the range of 150 bp upstream and downstream of each SNP site.

[0007] The second object of the present invention is to provide the application of the combined marker of SNP sites and methylation regions in the preparation of a product for evaluating the rejection risk after pancreas-kidney transplantation. The SNP sites include rs678476, rs7580884, rs200654741, rs4333131, rs57686994, rs1560173, rs13235115, rs1574122, rs797767, rs28972181, rs7142428, rs4074077, rs4395027, rs8026157, rs4984936, rs2303242, rs1107437, rs8064633, rs9912787, and rs7258301. The methylation region is the range of 150 bp upstream and downstream of each SNP site.

[0008] The third object of the present invention is to provide a kit for evaluating the rejection risk after pancreas-kidney transplantation. The kit targets SNP sites including rs678476, rs7580884, rs200654741, rs4333131, rs57686994, rs1560173, rs13235115, rs1574122, rs797767, rs28972181, rs7142428, rs4074077, rs4395027, rs8026157, rs4984936, rs2303242, rs1107437, rs8064633, rs9912787, and rs7258301.

[0009] Furthermore, the kit includes capture probes for capturing free DNA covering the SNP sites in the free DNA methylation library, specifically:

[0010] Probes for capturing cell-free DNA covering rs678476, with nucleotide sequences shown in SEQ ID NO.1-2;

[0011] Probes for capturing cell-free DNA covering rs7580884, with nucleotide sequences shown in SEQ ID NO.3-4;

[0012] Probes for capturing cell-free DNA covering rs200654741, with nucleotide sequences shown in SEQ ID NO.5-6;

[0013] Probes for capturing cell-free DNA covering rs4333131, with nucleotide sequences shown in SEQ ID NO.7-8;

[0014] Probes for capturing cell-free DNA covering rs57686994, with nucleotide sequences shown in SEQ ID NO.9-10;

[0015] Probes for capturing cell-free DNA covering rs1560173, with nucleotide sequences shown in SEQ ID NO.11-12;

[0016] Probes for capturing cell-free DNA covering rs13235115, with nucleotide sequences shown in SEQ ID NO.13-14;

[0017] Probes for capturing cell-free DNA covering rs1574122, with nucleotide sequences shown in SEQ ID NO.15-16;

[0018] Probes for capturing cell-free DNA covering rs797767, with nucleotide sequences shown in SEQ ID NO.17-18;

[0019] Probes for capturing cell-free DNA covering rs28972181, with nucleotide sequences shown in SEQ ID NO.19-20;

[0020] Probes for capturing cell-free DNA covering rs7142428, with nucleotide sequences shown in SEQ ID NO.21-22;

[0021] Probes for capturing cell-free DNA covering rs4074077, with nucleotide sequences shown in SEQ ID NO.23-24;

[0022] Probes for capturing cell-free DNA covering rs4395027, with nucleotide sequences shown in SEQ IDNO.25-26;

[0023] Probes for capturing cell-free DNA covering rs8026157, with nucleotide sequences shown in SEQ ID NO.27-28;

[0024] Probes for capturing cell-free DNA covering rs4984936, with nucleotide sequences shown in SEQ ID NO.29-30;

[0025] Probes for capturing cell-free DNA covering rs2303242, with nucleotide sequences shown in SEQ ID NO.31-32;

[0026] Probes for capturing cell-free DNA covering rs1107437, with nucleotide sequences shown in SEQ ID NO.33-34;

[0027] Probes for capturing cell-free DNA covering rs8064633, with nucleotide sequences shown in SEQ ID NO.35-36;

[0028] Probes for capturing cell-free DNA covering rs9912787, with nucleotide sequences shown in SEQ ID NO.37-38;

[0029] Probes for capturing cell-free DNA covering rs7258301, with nucleotide sequences shown in SEQ ID NO.39-40.

[0030] Furthermore, the 5'-end of the capture probe is labeled with biotin.

[0031] Furthermore, the kit contains streptavidin magnetic beads.

[0032] Furthermore, the kit includes primers for sequencing, with nucleotide sequences shown in SEQ ID NO.41-42.

[0033] The fourth object of the present invention is to provide a detection method for the above-mentioned kit, comprising the following steps:

[0034] Step S1: Extract cell-free DNA from the sample to be tested, perform methylation conversion on the cell-free DNA to obtain a cell-free DNA methylation library;

[0035] Step S2: Hybridize the cell-free DNA methylation library with the capture probe to obtain a hybrid capture library, and elute the cell-free DNA methylation library that has not bound to the capture probe;

[0036] Step S3: Sequence the hybrid capture library, calculate the relative values of kidney-derived cell-free DNA and pancreas-derived cell-free DNA in the sample to be tested according to the sequencing results, so as to determine whether there is a risk of pancreas rejection and / or kidney rejection in the sample to be tested.

[0037] Further, in step S3, the method for calculating the relative values of kidney-derived free DNA and pancreas-derived free DNA in the sample to be tested according to the sequencing results specifically includes:

[0038] Step S31: Calculate the variant allele frequency of the SNP locus according to the sequencing results. Select the SNP locus with a variant allele frequency between 0 and 0.1 as the effective SNP locus;

[0039] Step S32: Calculate the relative value of donor-derived free DNA according to the variant allele frequency of the effective SNP locus;

[0040] Step S33: Calculate the average methylation level of donor-derived free DNA;

[0041] Step S34: Obtain the methylation maps of the pancreas tissue and the kidney tissue respectively;

[0042] Step S35: Calculate the relative values of kidney-derived free DNA and pancreas-derived free DNA respectively according to the methylation maps, so as to determine whether the sample to be tested has pancreatic rejection and / or kidney rejection.

[0043] Further, in step S31, the method for calculating the variant allele frequency is:

[0044]

[0045] Further, in step S32, the method for calculating the relative value of donor-derived free DNA is:

[0046]

[0047] The fifth object of the present invention is to provide the use of a probe composition in the preparation of a product for evaluating the risk of graft rejection after combined pancreas-kidney transplantation. The probe composition is as follows:

[0048] A probe for capturing free DNA covering the SNP locus rs678476, the nucleotide sequence is shown in SEQ ID NO.1-2;

[0049] A probe for capturing free DNA covering the SNP locus rs7580884, the nucleotide sequence is shown in SEQ ID NO.3-4;

[0050] A probe for capturing free DNA covering the SNP locus rs200654741, the nucleotide sequence is shown in SEQ IDNO.5-6;

[0051] A probe for capturing free DNA covering the SNP locus rs4333131, the nucleotide sequence is shown in SEQ ID NO.7-8;

[0052] Probes for capturing cell-free DNA covering SNP locus rs57686994, with nucleotide sequences as shown in SEQ ID NO.9-10;

[0053] Probes for capturing cell-free DNA covering SNP locus rs1560173, with nucleotide sequences as shown in SEQ ID NO.11-12;

[0054] Probes for capturing cell-free DNA covering SNP locus rs13235115, with nucleotide sequences as shown in SEQ ID NO.13-14;

[0055] Probes for capturing cell-free DNA covering SNP locus rs1574122, with nucleotide sequences as shown in SEQ ID NO.15-16;

[0056] Probes for capturing cell-free DNA covering SNP locus rs797767, with nucleotide sequences as shown in SEQ ID NO.17-18;

[0057] Probes for capturing cell-free DNA covering SNP locus rs28972181, with nucleotide sequences as shown in SEQ ID NO.19-20;

[0058] Probes for capturing cell-free DNA covering SNP locus rs7142428, with nucleotide sequences as shown in SEQ ID NO.21-22;

[0059] Probes for capturing cell-free DNA covering SNP locus rs4074077, with nucleotide sequences as shown in SEQ ID NO.23-24;

[0060] Probes for capturing cell-free DNA covering SNP locus rs4395027, with nucleotide sequences as shown in SEQ ID NO.25-26;

[0061] Probes for capturing cell-free DNA covering SNP locus rs8026157, with nucleotide sequences as shown in SEQ ID NO.27-28;

[0062] Probes for capturing cell-free DNA covering SNP locus rs4984936, with nucleotide sequences as shown in SEQ ID NO.29-30;

[0063] Probes for capturing cell-free DNA covering SNP locus rs2303242, with nucleotide sequences as shown in SEQ ID NO.31-32;

[0064] Probes for capturing cell-free DNA covering SNP locus rs1107437, with nucleotide sequences as shown in SEQ ID NO.33-34;

[0065] Probes for capturing cell-free DNA covering SNP locus rs8064633, with nucleotide sequences as shown in SEQ ID NO.35-36;

[0066] Probes for capturing cell-free DNA covering SNP locus rs9912787, with nucleotide sequences as shown in SEQ ID NO.37-38;

[0067] Probes for capturing cell-free DNA covering SNP locus rs7258301, with nucleotide sequences as shown in SEQ ID NO.39-40.

[0068] Advantages of the present invention:

[0069] By screening, the present invention obtains 20 SNP locus-methylation region combined markers, which can distinguish cell-free DNA from the pancreas and kidney, realize independent evaluation of the risk of dual-organ rejection. Based on the detection of cell-free DNA in peripheral blood, it avoids the invasiveness and complication risks of traditional biopsies. Probe capture combined with methylation analysis significantly improves the detection sensitivity of donor DNA and the ability of organ-specific recognition, can detect subclinical rejection at an early stage, and the standardized operation process of the supporting kit is compatible with conventional sequencing platforms, shortening the detection cycle and facilitating clinical promotion. Description of the Drawings

[0070] In order to make the content of the present invention easier to be clearly understood, the following further details the present invention according to specific embodiments of the present invention in combination with the drawings, where

[0071] Figure 1 are the detection results of the SMT_NNLS method and the WGBS_NNLS method in Example 4 of the present invention;

[0072] Figure 2 is the confusion matrix of the detection results of the SMT_NNLS method in Example 4 of the present invention;

[0073] Figure 3 is the confusion matrix of the detection results of the WGBS_NNLS method in Example 4 of the present invention. Detailed Embodiments

[0074] The following further illustrates the present invention in combination with the drawings and specific embodiments, so that those skilled in the art can better understand the present invention and be able to implement it, but the examples given are not intended to limit the present invention.

[0075] Example 1: Screening of SNP Site-Methylation Region Combined Markers and Probe Design

[0076] (1) Screening of Biallelic SNPs

[0077] Screen biallelic SNPs from the dbSNP (Single Nucleotide Polymorphism Database). It is required that the allelic frequency of the mutated base at this variant site in the East Asian population of the 1000 Genomes Project data is between 0.4 and 0.6, and SNPs that overlap with CpG sites are removed to avoid errors in subsequent call SNP and call methylation;

[0078] (2) Ensuring Regional CpG Density

[0079] Centered on each biallelic SNP, expand the ±150bp region, and retain regions covering ≥4 CpGs, for a total of 274,886 regions;

[0080] (3) Obtaining Methylation Data

[0081] Download the whole-genome DNA methylation sequencing (WGBS) data (GSE186458) of primary kidney cells and primary pancreatic cells from healthy individuals, and the reduced-representation bisulfite sequencing (RRBS) data (GSE233417) of kidney tissues and pancreatic tissues from healthy individuals published in the GEO (Gene Expression Omnibus) database. The sample types and corresponding sample numbers used are shown in Table 1.

[0082] Table 1 Sample Types and Sample Numbers

[0083] Sample type Number of samples Sample type Number of samples Kidney tissue 13 Pancreas tissue 14 Glomerular parietal epithelial cells 2 Pancreatic endothelial cells 3 Glomerular endothelial cells 3 Islet endothelial cells 1 Visceral epithelial cells of renal capsule 3 Pancreatic duct cells 4 Renal tubular epithelial cells 3 Pancreatic acinar cells 4 Renal tubular endothelial cells 3 Pancreatic alpha cells 3 Pancreatic beta cells 3 Pancreatic delta cells 3

[0084] (4) Methylation Difference Analysis at the Tissue Level

[0085] For the above 274,886 regions, calculate the average methylation levels of 14 pancreatic tissue samples and 13 kidney tissue samples, including the mean, 80th percentile, and 20th percentile. Retain regions that meet any of the following conditions:

[0086] Condition 1: The mean of the average methylation level of the pancreatic sample group is lower than that of the kidney sample group, and the difference between the two is greater than 0.3, and the statistical significance P value is less than 0.01; in addition, the 80th percentile of the average methylation level of the pancreatic sample group is lower than the 20th percentile of the kidney sample group, and the difference is greater than 0.3;

[0087] Condition 2: The average of the mean methylation levels of the kidney sample group is lower than that of the pancreas sample group, and the difference between the two is greater than 0.3, while the statistical significance P-value is less than 0.01; in addition, the 80th percentile of the mean methylation level of the kidney sample group is lower than the 20th percentile of the pancreas sample group, and the difference is greater than 0.3.

[0088] (5) Methylation difference analysis at the cellular level

[0089] Calculate the average of the mean methylation levels of different primary cell samples of the pancreas and different primary cell samples of the kidney in the above regions respectively. Retain the regions that meet the following conditions:

[0090] The difference between the average of the mean methylation levels of the pancreas cell sample group and the corresponding value of the kidney cell sample group is greater than 0.3, and the P-value is less than 0.01; at the same time, the standard deviations of the mean methylation levels of both the pancreas cell sample group and the kidney cell sample group are less than 0.15.

[0091] (6) Calculate the regional difference score (Δβ-score)

[0092] Δβ-score = |KT mean - PT mean | + |KC mean - PC mean | - |KC std - PC std |

[0093] where KT mean is the average of the methylation levels of the kidney tissue sample group, PT mean is the average of the methylation levels of the pancreas tissue sample group, KC mean is the average of the methylation levels of the kidney cell sample group, PC mean is the average of the methylation levels of the pancreas cell sample group, KC std is the standard deviation of the methylation levels of the kidney cell sample group, PC std is the standard deviation of the methylation levels of the pancreas cell sample group.

[0094] (7) Region screening and retention

[0095] Delete highly homologous regions to avoid difficulties in probe design; and within each 1000bp window, only retain the region with the highest Δβ-score to reduce redundancy and interference; delete the regions on the sex chromosomes to minimize potential changes in methylation levels caused by different sex chromosome dosages, and finally retain 20 regions as SNP-methylation combined markers.

[0096] (8) Determine the probe capture strand and design probes

[0097] When the SNP type is C>T, after methylation sequencing, since it is impossible to accurately distinguish methylated C from the true T base, this will lead to errors in identifying (calling) SNP signals. Therefore, the capture of the OT (top strand) is not feasible; however, this limitation has no impact on the OB (bottom strand). The reason is that on the OB strand, the corresponding SNP type is G>A, and after methylation sequencing, the sequencing result shows a comparison between C and T (that is, the original G is paired with C after complementary pairing, and A is paired with T after complementary pairing, but the bases on the complementary strand are concerned during sequencing, so it shows a comparison between C and T). Table 2 details all dimorphic SNP types (Ref and Alt) and the sequencing results of different strands (the bases that can be considered for actual call SNP) as well as the corresponding probe capture strand selection under the condition of capturing different strands. Table 3 lists the detailed information of 20 biomarker regions and the probe sequences, where the 5' ends of the probes described in the table are all linked to biotin.

[0098] Table 2 Sequencing Results of Different Captured Strands

[0099]

[0100] Table 3 60 Biomarker Regions and Probe Sequences

[0101]

[0102] Example 2: cfDNA Extraction, Methylation Library Construction, Hybridization Capture and Sequencing I. cfDNA Extraction

[0103] Using blood cfDNA as the sample to be tested, use a cell-free DNA extraction kit ( CirculatingNucleic Acid, QIAGEN) to extract the cell-free DNA in the sample to be tested; according to the instructions of the Qubit dsDNA HS Assay Kit DNA concentration quantification kit, use a Qubit 3.0 Fluorometer (Thermo Fisher) to measure the concentration of the extracted cfDNA sample.

[0104] II. cfDNA Methylation Double-Strand Library Construction

[0105] The cfDNA methylation library construction method uses the YEASEN double-stranded DNA methylation library construction kit (12214ES) to construct a DNA library, and the library construction operation is carried out with reference to the product instructions of the kit. Among them, the methylation conversion processing module selects the ZYMO RESEARCH bisulfite conversion kit (Zymo EZ DNA methylation kit, D500).

[0106] III. Hybrid Capture of the Converted Library

[0107] (1) Library Mixing, Blocking, and Concentration

[0108] Mix the reagents and the library in a 0.2 mL PCR tube according to the following ratio

[0109] Table 4 Mixing Ratio

[0110] Single library or mixed library 500 ng Human Cot-1DNA 5 μg Un-Blocker 2 μL

[0111] Vortex thoroughly to mix, and then centrifuge briefly to the bottom of the tube

[0112] Place the mixture in the PCR tube on a vacuum rotary evaporator and evaporate the reaction solution at 55 - 60 °C until dry

[0113] (2) Library Hybridization

[0114] Table 5 Reaction System

[0115] HYB-buffer 10 uL Enhancer 2 uL Capture probe Probe 2 uL <![CDATA[Nuclear-Free H2O]]> 2 uL

[0116] After thoroughly pipetting and mixing with a pipette, let it stand at room temperature for 5 - 10 min, then pipette and mix again, and centrifuge briefly; place it in a PCR instrument and react at 95 °C for 5 min and 65 °C for 2 hours

[0117] (3) Binding of the Library to Streptavidin Magnetic Beads

[0118] Mix the SA Beads streptavidin magnetic beads with the reaction solution in (2) in a 65 °C PCR instrument thoroughly and react for 30 min. During this period, take out the PCR tube every 10 min, quickly vortex for 5 seconds, and immediately put it back into the PCR instrument

[0119] (4) Elution

[0120] Use the prepared Wash buffer to elute the unbound DNA library

[0121] Hot elution at 65 °C: Add 120 μL of preheated 1XW1 wash solution at 65 °C to the PCR tube after step (3). Use a pipette to repeatedly pipette and mix. Incubate at 65 °C for 10 - 20 sec. Place the PCR tube on a magnetic stand, quickly separate the magnetic beads from the supernatant, and discard the supernatant

[0122] Use 150 μL of preheated SW wash solution at 65 °C, slowly pipette 10 - 15 times to fully suspend the SA magnetic beads. Place the PCR tube back on the PCR instrument and incubate at 65 °C for 5 min with precise timing, then place the PCR on the magnetic stand, separate and discard the supernatant. Repeat the above SW wash once

[0123] Room temperature elution: Add 150 μL of 1X W1 wash buffer to the PCR tube containing SA magnetic beads in the above step, vortex for a total of 2 min to fully suspend the magnetic beads. Place on a magnetic stand to separate the supernatant of the magnetic beads and discard the supernatant. Add 150 μL of 1X W2 wash buffer, vortex for 1 min to fully suspend. Place on a magnetic stand to separate the supernatant of the magnetic beads and discard the supernatant. Add 150 μL of 1X W3 wash buffer, vortex for 1 min to fully suspend. Place on a magnetic stand to separate the supernatant of the magnetic beads and discard the supernatant. Add 23 μL of Nuclear-Free H2O to the remaining magnetic beads to resuspend the magnetic beads.

[0124] (5) POST-PCR

[0125] Add sequencing platform adapters and perform a PCR reaction to complete the preparation of the hybridization capture library.

[0126] The primer sequences (5’-3’) are P5: p-AATGATACGGCGACCACCGAGATC (shown in SEQ ID NO.41);

[0127] P7: CAAGCAGAAGACGGCATACGAGAT (shown in SEQ ID NO.42).

[0128] Prepare the reaction solution according to the following system:

[0129] Table 6 Reaction solution preparation

[0130] 2X HIFI Enzyme 25 uL MGIPRIMER 2 uL Magnetic bead resuspension 23 uL

[0131] Place the PCR tube in a PCR instrument, set the reaction program, and perform PCR amplification. The amplification program: 98°C for 45 s, 98°C for 15 sec, 50°C for 30 sec, 72°C for 30 sec, 72°C for 1 min, with 17 cycles of circular reaction. After PCR, purify and recover the amplification products using magnetic beads. The magnetic bead recovery steps are the same as in (3). Quantitatively control the concentration of the amplified library, and perform on-machine sequencing (PE150) on the POST-PCR library products.

[0132] Example 3: Tissue traceability algorithm SMT_NNLS (SNP-Methylation Target_capture NNLS)

[0133] (1) Pre-data processing:

[0134] Perform quality control on the downloaded data and remove the adapter sequences, use the bismark software for sequence alignment, and remove duplicates;

[0135] (2) Call SNP signals

[0136] Merge the read1 and read2 at the same chip position in paired-end sequencing into a single sequence (merged_read), and remove sequences with abnormal insert sizes: < 30bp or > 500bp;

[0137] For each SNP-methylation marker, based on the position of the SNP, find all merged_reads covering that position, extract the base at the SNP position, and classify it as ref or alt according to Table 2;

[0138] Record the read counts of ref and alt at the SNP, ref_depth and alt_depth, for each SNP-methylation marker, and exclude SNP sites with a total depth of less than 300X;

[0139] Genotype the remaining SNP sites, and screen SNP sites where the recipient genotype is homozygous and there are small signals as valid SNP sites. That is, if the recipient is of AA type, the donor is of Aa or aa type, and calculate the Variant Allele Frequency (VAF):

[0140]

[0141] It is required that 0 < VAF < 0.1.

[0142] (3) Calculate the relative value of ddcfDNA

[0143] Sort the VAFs of all valid sites from smallest to largest and denote them as v1, v2,..., v N (N is the number of valid sites). According to Mendel's genetic law, 2 / 3 of the valid sites are recipient AA homozygous and donor Aa heterozygous; 1 / 3 of the valid sites are recipient AA homozygous and donor aa homozygous; and the VAF of the SNP where the donor is of Aa type is 1 / 2 of that where the donor is of aa type. Calculate the relative value of ddcfDNA based on this.

[0144]

[0145] (4) Calculate the average methylation level of donor cfDNA in the marker regions where the valid sites are located

[0146] The merged_reads with the base at the SNP site identical to the donor base are the determined donor cfDNA. Calculate C_count / (T_count + C_count) at all CpG positions within each marker region, and take it as the average methylation level of this marker, denoted as m = [m1, m2,..., m N

[0147] ​(5) Obtain the methylation profiles A of pancreatic and renal tissues

[0148]

[0149] where A 1i , A 2i are the average methylation levels of renal and pancreatic tissues on the i-th biomarker group, respectively.

[0150] (6) Calculate the relative values of renal cfDNA and pancreatic cfDNA

[0151] Use the least squares method to solve for X = [X1, X2] such that ||A T X - m T ||2 is minimized;

[0152] Renal

[0153] Pancreas

[0154] Example 4: Test results of clinical samples

[0155] (1) Sample collection: 15 patients who underwent simultaneous pancreas-kidney transplantation with pancreas-kidney biopsy, including 5 patients with no rejection, 3 patients with renal rejection only, 3 patients with pancreatic rejection only, and 4 patients with both rejections

[0156] (2) Extract cfDNA and construct cfDNA methylation libraries for the above samples respectively;

[0157] (3) Hybridize and capture and sequence the above samples, and calculate the relative values of renal cfDNA and pancreatic cfDNA using the SMT_NNLS (SNP-methylation combined tracing) method of the present invention. The detection results are as Figure 1 shown, and the confusion matrix is as Figure 2 shown;

[0158] (4) Perform whole-genome methylation sequencing on the above samples. The average sequencing depth is 10.2X (7.8X - 12.7X). Calculate the average methylation level of each sample in 5820 methylation regions (see the literature Plasma DNA tissue mapping by genome-wide methylation sequencing for noninvasive prenatal, cancer, and transplantation assessments, PNAS), and calculate the relative values of renal cfDNA and pancreatic cfDNA using the NNLS algorithm. The detection results are as Figure 1 shown, and the confusion matrix is as Figure 2 shown;

[0159] As can be seen from the detection results and the confusion matrix, the SMT_NNLS (SNP-methylation combined targeted traceability) method provided by the present invention has the ability to distinguish multiple categories with high precision, and the overall accuracy rate is increased by 62.5% (Table 7):

[0160] In 15 clinical samples, the accuracy rate of the SMT method reached 81.25%, which was significantly better than 50% of the traditional WGBS_NNLS method;

[0161] For simple pancreatic rejection detection: the recall rate of SMT_NNLS reached 100%, while the WGBS_NNLS method was 33.33%;

[0162] For simple kidney rejection detection: the precision rate of SMT_NNLS reached 75%, while the WGBS_NNLS method was 40%;

[0163] For both rejection detections: the recall rate was increased to 66.67%, while the WGBS_NNLS method was 50%, significantly reducing the risk of missed diagnosis;

[0164] For both non-rejection detections: the precision rate was increased to 100%, while the WGBS_NNLS method was 66.67%, effectively avoiding over-treatment caused by false positives.

[0165] Table 7 Comparison of detection indexes of different methods

[0166] Index SMT_NNLS WGBS_NNLS Accuracy 0.8125 0.5 Macro-average F1 0.8161 0.4876 Weighted average F1 0.8156 0.5037 All non-rejection - Precision 1 0.6667 Simple renal rejection - Precision 0.75 0.4 Simple pancreatic rejection - Precision 0.6 0.3333 All rejection - Precision 1 0.6 All non-rejection - Recall 0.75 0.5 Simple renal rejection - Recall 1 0.6667 Simple pancreatic rejection - Recall 1 0.3333 All rejection - Recall 0.6667 0.5

[0167] Obviously, the above embodiments are only examples for clear illustration and are not limitations on the implementation manners. For those of ordinary skill in the art, other different forms of changes or modifications can be made based on the above description. It is not necessary and impossible to enumerate all the implementation manners here. And the obvious changes or modifications derived therefrom are still within the protection scope of the present invention.

Claims

1. A SNP site-methylation region joint marker combination for assessing the risk of rejection after combined pancreas-kidney transplantation, characterized in that: The SNP sites include rs678476, rs7580884, rs200654741, rs4333131, rs57686994, rs1560173, rs13235115, rs1574122, rs797767, rs28972181, rs7142428, rs4074077, rs4395027, rs8026157, rs4984936, rs2303242, rs1107437, rs8064633, rs9912787 and rs7258301, and the methylation region is 150bp upstream and downstream of the SNP site.

2. Use of a SNP site-methylation region joint marker combination in the preparation of a product for assessing the risk of rejection after combined pancreas-kidney transplantation, characterized in that: The SNP sites include rs678476, rs7580884, rs200654741, rs4333131, rs57686994, rs1560173, rs13235115, rs1574122, rs797767, rs28972181, rs7142428, rs4074077, rs4395027, rs8026157, rs4984936, rs2303242, rs1107437, rs8064633, rs9912787 and rs7258301, and the methylation region is 150bp upstream and downstream of the SNP site.

3. A kit for assessing the risk of rejection after combined pancreas-kidney transplantation, characterized in that: The kit targets SNP sites including rs678476, rs7580884, rs200654741, rs4333131, rs57686994, rs1560173, rs13235115, rs1574122, rs797767, rs28972181, rs7142428, rs4074077, rs4395027, rs8026157, rs4984936, rs2303242, rs1107437, rs8064633, rs9912787 and rs7258301.

4. The kit according to claim 3, characterized in that The kit includes a capture probe for capturing free DNA covering the SNP site in the free DNA methylation library, specifically: A probe for capturing free DNA covering rs678476, the nucleotide sequence of which is shown in SEQ ID NO.1-2; A probe for capturing free DNA covering rs7580884, the nucleotide sequence of which is shown in SEQ ID NO.3-4; A probe for capturing free DNA covering rs200654741, the nucleotide sequence of which is shown in SEQ ID NO.5-6; A probe for capturing free DNA covering rs4333131, the nucleotide sequence of which is shown in SEQ ID NO.7-8; A probe for capturing free DNA covering rs57686994, the nucleotide sequence of which is shown in SEQ ID NO.9-10; A probe for capturing free DNA covering rs1560173, the nucleotide sequence of which is shown in SEQ ID NO.11-12; A probe for capturing free DNA covering rs13235115, the nucleotide sequence of which is shown in SEQ ID NO.13-14; A probe for capturing free DNA covering rs1574122, the nucleotide sequence of which is shown in SEQ ID NO.15-16; A probe for capturing free DNA covering rs797767, the nucleotide sequence of which is shown in SEQ ID NO.17-18; The probe used to capture free DNA covering rs28972181, the nucleotide sequence is shown in SEQ ID NO.19-20; A probe for capturing free DNA covering rs7142428, the nucleotide sequence of which is shown in SEQ ID NO.21-22; A probe for capturing free DNA covering rs4074077, the nucleotide sequence of which is shown in SEQ ID NO.23-24; A probe for capturing free DNA covering rs4395027, the nucleotide sequence of which is shown in SEQ ID NO.25-26; A probe for capturing free DNA covering rs8026157, the nucleotide sequence of which is shown in SEQ ID NO.27-28; A probe for capturing free DNA covering rs4984936, the nucleotide sequence of which is shown in SEQ ID NO. 29-30; A probe for capturing free DNA covering rs2303242, the nucleotide sequence of which is shown in SEQ ID NO.31-32; A probe for capturing free DNA covering rs1107437, the nucleotide sequence of which is shown in SEQ ID NO.33-34; A probe for capturing free DNA covering rs8064633, the nucleotide sequence of which is shown in SEQ ID NO.35-36; A probe for capturing free DNA covering rs9912787, the nucleotide sequence of which is shown in SEQ ID NO.37-38; The probe used to capture free DNA covering rs7258301, the nucleotide sequence is shown in SEQ ID NO.39-40.

5. The kit according to claim 4, characterized in that: The 5' end of the capture probe is labeled with biotin.

6. The kit according to claim 5, characterized in that: The kit contains streptavidin magnetic beads.

7. The kit according to claim 3, characterized in that: The kit includes primers for sequencing, and the nucleotide sequences of the primers are shown in SEQ ID NOs.41-42.

8. The detection method of the kit according to any one of claims 3 to 7, characterized in that: The following steps are involved: Step S1, extracting free DNA from the sample to be tested, performing methylation conversion on the free DNA, and obtaining a free DNA methylation library; Step S2, hybridizing the free DNA methylation library with the capture probe to obtain a hybrid capture library, and eluting the free DNA methylation library that is not bound to the capture probe; Step S3, sequencing the hybridization capture library, and calculating the relative values ​​of kidney-derived free DNA and pancreatic-derived free DNA in the sample to be tested based on the sequencing results, so as to determine whether the sample to be tested has a risk of pancreatic rejection and / or kidney rejection.

9. The detection method according to claim 8, characterized in that: In step S3, the method for calculating the relative values ​​of kidney-derived free DNA and pancreatic-derived free DNA in the sample to be tested according to the sequencing results specifically includes: Step S31, screening effective SNP sites of homozygous receptor genes according to sequencing results, and calculating variant allele frequencies of the effective SNP sites; Step S32, calculating the relative value of donor-derived free DNA according to the variant allele frequency of the effective SNP site; Step S33, calculating the average methylation level of donor-derived free DNA; Step S34, respectively obtaining methylation profiles of pancreatic tissue and kidney tissue; Step S35, respectively calculating the relative value of kidney-derived free DNA and the relative value of pancreatic-derived free DNA according to the methylation spectrum, so as to determine whether the sample to be tested has pancreatic rejection and / or kidney rejection.

10. Use of a probe composition in the preparation of a product for assessing the risk of graft rejection after combined pancreas-kidney transplantation, characterized in that: The probe composition is as follows: A probe for capturing free DNA covering the SNP site rs678476, the nucleotide sequence of which is shown in SEQ ID NO.1-2; A probe for capturing free DNA covering the SNP site rs7580884, the nucleotide sequence of which is shown in SEQ ID NO.3-4; A probe for capturing free DNA covering the SNP site rs200654741, the nucleotide sequence of which is shown in SEQ ID NO.5-6; A probe for capturing free DNA covering the SNP site rs4333131, the nucleotide sequence of which is shown in SEQ ID NO.7-8; A probe for capturing free DNA covering the SNP site rs57686994, the nucleotide sequence of which is shown in SEQ ID NO.9-10; A probe for capturing free DNA covering the SNP site rs1560173, the nucleotide sequence of which is shown in SEQ ID NO.11-12; A probe for capturing free DNA covering the SNP site rs13235115, the nucleotide sequence of which is shown in SEQ ID NO.13-14; A probe for capturing free DNA covering the SNP site rs1574122, the nucleotide sequence of which is shown in SEQ ID NO.15-16; A probe for capturing free DNA covering the SNP site rs797767, the nucleotide sequence of which is shown in SEQ ID NO.17-18; A probe for capturing free DNA covering the SNP site rs28972181, the nucleotide sequence of which is shown in SEQ ID NO. 19-20; A probe for capturing free DNA covering the SNP site rs7142428, the nucleotide sequence of which is shown in SEQ ID NO. 21-22; A probe for capturing free DNA covering the SNP site rs4074077, the nucleotide sequence of which is shown in SEQ ID NO. 23-24; A probe for capturing free DNA covering the SNP site rs4395027, the nucleotide sequence of which is shown in SEQ ID NO. 25-26; A probe for capturing free DNA covering the SNP site rs8026157, the nucleotide sequence of which is shown in SEQ ID NO. 27-28; A probe for capturing free DNA covering the SNP site rs4984936, the nucleotide sequence of which is shown in SEQ ID NO. 29-30; A probe for capturing free DNA covering the SNP site rs2303242, the nucleotide sequence of which is shown in SEQ ID NO.31-32; A probe for capturing free DNA covering the SNP site rs1107437, the nucleotide sequence of which is shown in SEQ ID NO.33-34; A probe for capturing free DNA covering the SNP site rs8064633, the nucleotide sequence of which is shown in SEQ ID NO.35-36; A probe for capturing free DNA covering the SNP site rs9912787, the nucleotide sequence of which is shown in SEQ ID NO.37-38; The probe used to capture free DNA covering the SNP site rs7258301, the nucleotide sequence is shown in SEQ ID NO.39-40.

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